AI-Driven Biophilic Façade Design for Senior Multi-Family Housing Using LoRA and Stable Diffusion

South Korea is rapidly transitioning into an aging society, resulting in a growing demand for senior multi-family housing. Nevertheless, current façade designs remain limited in diversity and fail to adequately address the visual needs and preferences of the elderly population. This study presents a biophilic façade design approach for senior housing, utilizing Stable Diffusion (SD) fine-tuned with low-rank adaptation (LoRA) to support the implementation of differentiated biophilic design (BD) strategies. Prompts were derived from an analysis of Korean and worldwide cases, reflecting the perceptual and cognitive characteristics of older adults. A dataset focusing on key BD attributes—specifically color and shapes/forms—was constructed and used to train the LoRA model. To enhance accuracy and contextual relevance in image generation, ControlNet was applied. The validity of the dataset was evaluated through expert assessments using Likert-scale analysis, while model reliability was examined using loss function trends and Frechet Inception Distance (FID) scores. Our findings indicate that the proposed approach enables more precise and scalable applications of biophilic design in senior housing façades. This approach highlights the potential of AI-assisted design workflows in promoting age-inclusive and biophilic urban environments.